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Research map / Label-efficient and robust learning / Knowledge distillation

Progressive Teacher-Student Learning for Early Action Prediction

CVPR 2019 · Label-efficient and robust learning › Knowledge distillation · approach: Teacher properties and robustness · 141 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add progressive teacher-student knowledge distillation (ablation)STUDENT early-action model · NTU RGB-D ActionAUC (%): 59.24 -> 60.97Helped
add progressive teacher-student knowledge distillation (ablation)STUDENT early-action model · SYSU 3DHOIAUC (%): 71.87 -> 75.35Helped
add progressive teacher-student knowledge distillation (ablation)STUDENT early-action model · UCF-101AUC (%): 88.39 -> 89.64Helped
add local MSE distillation (ablation)STUDENT early-action model · SYSU 3DHOIAUC (%): 71.87 -> 73.53Helped
add global MMD distillation (ablation)STUDENT early-action model · SYSU 3DHOIAUC (%): 71.87 -> 73.08Helped
combine local MSE and global MMD distillation (ablation)STUDENT early-action model · SYSU 3DHOIAUC (%): 71.87 -> 75.35Helped
add local MSE distillation (ablation)STUDENT early-action model · UCF-101AUC (%): 88.39 -> 89.27Helped
add global MMD distillation (ablation)STUDENT early-action model · UCF-101AUC (%): 88.39 -> 89.01Helped
combine local MSE and global MMD distillation (ablation)STUDENT early-action model · UCF-101AUC (%): 88.39 -> 89.64Helped
use two-stage rather than one-stage optimization (ablation)teacher-student model · SYSU 3DHOIAUC (%): 73.57 -> 75.35Helped
use two-stage rather than one-stage optimization (ablation)teacher-student model · UCF-101AUC (%): 89.51 -> 89.64Helped
train teacher and student jointly instead of fixing a pretrained teacher (ablation)teacher-student model · SYSU 3DHOIAUC (%): 75.35 -> 72.49Hurt

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